Chapter 2: The Research Enterprise in Psychology

1. Chapter 2: The Research Enterprise in Psychology

2. The Scientific Approach:A Search for Laws • Basic assumption: events are governed by some lawful order • Goals: • Measurement and description • Understanding and prediction • Application and control

3. Figure 2.1 Theory construction

4. Figure 2.2 Flowchart of steps in a scientific investigation

5. The Scientific Method: Terminology • Operational definitions are used to clarify precisely what is meant by each variable. Example: Lower scores on the Beck Depression Inventory = lower levels of depression • Participants or subjects are the organisms whose behavior is systematically observed in a study • Data collection techniques allow for empirical observation and measurement • Statistics are used to analyze data and decide whether hypotheses were supported

6. The Scientific Method: Terminology • Findings are shared through reports at scientific meetings and in scientific journals – periodicals that publish technical and scholarly material • Advantages of the scientific method: clarity of communication and relative intolerance of error • Research methods: general strategies for conducting scientific studies

7. Table 2.1 Key Data Collection Techniques in Psychology

8. Experimental Research:Looking for Causes • Experiment = manipulation of one variable under controlled conditions so that resulting changes in another variable can be observed • Detection of cause-and-effect relationships • Independent variable (IV) = variable manipulated • Dependent variable (DV) = variable affected by manipulation • How does X affect Y? • X = Independent Variable, and Y = Dependent Variable

9. Experimental and Control Groups:The Logic of the Scientific Method • Experimental group: group that receives the “treatment” (some change in the I.V.) • Control group: does not experience the change in the I.V. • Random assignment • Manipulate independent variable for one group only • Resulting differences in the two groups must be due to the independent variable

10. Extraneous and confounding variables • Crime rate is associated with ice cream sales • Crime rate is associated with the number of churches per square mile

11. Figure 2.5 The basic elements of an experiment

12. Experimental Designs: Variations • Expose a single group to two different conditions • Reduces extraneous variables • Manipulate more than one independent variable - Allows for study of interactions between variables • Use more than one dependent variable - Obtains a more complete picture of effect of the independent variable

13. Figure 2.6 Manipulation of two independent variables in an experiment

14. Strengths and Weaknessesof Experimental Research • Strengths: • conclusions about cause-and-effect can be drawn • Weaknesses: • artificial nature of experiments • ethical and practical issues

15. Descriptive/Correlational Methods:Looking for Relationships • Methods used when a researcher cannot manipulate the variables under study • Naturalistic observation • Case studies • Surveys • Allow researchers to describe patterns of behavior and discover links or associations between variables but cannot imply causation

16. Figure 2.10 Comparison of major research methods

17. Statistics and Research:Drawing Conclusions • Statistics – using mathematics to organize, summarize, and interpret numerical data • Descriptive statistics: organizing and summarizing data • Inferential statistics: interpreting data and drawing conclusions

18. Descriptive Statistics:Measures of Central Tendency • Measures of central tendency = typical or average score in a distribution • Mean: arithmetic average of scores • Median: score falling in the exact center • Mode: most frequently occurring score • Which most accurately depicts the typical?

19. Figure 2.11 Measures of central tendency

20. Descriptive Statistics:Variability • Variability = how much scores vary from each other and from the mean • Standard deviation = numerical depiction of variability • High variability in data set = high standard deviation • Low variability in data set = low standard deviation

21. Figure 2.12 Variability and the standard deviation

22. Descriptive Statistics: Correlation • When two variables are related to each other, they are correlated. • Correlation = numerical index of degree of relationship • Correlation expressed as a number between 0 and 1 • Can be positive or negative • Numbers closer to 1 (+ or -) indicate stronger relationship

23. Figure 2.14 Interpreting correlation coefficients

24. Correlation:Prediction, Not Causation • Higher correlation coefficients = increased ability to predict one variable based on the other • SAT/ACT scores moderately correlated with first year college GPA • 2 variables may be highly correlated, but not causally related • Foot size and vocabulary positively correlated • Do larger feet cause larger vocabularies? • The third variable problem

25. Figure 2.15 Three possible causal relationships between correlated variables

26. Inferential Statistics:Interpreting Data and Drawing Conclusions • Hypothesis testing: do observed findings support the hypotheses? • Are findings real or due to chance? • Statistical significance = when the probability that the observed findings are due to chance is very low • Very low = less than 5 chances in 100/ .05 level

27. Evaluating Research:Methodological Pitfalls • Sampling bias: sample is not representative of the population • Placebo effects: the subject’s expectations lead them to experience change

28. Evaluating Research:Methodological Pitfalls • Distortions in self-report data: • Social desirability bias: the tendency to give socially approved answers to questions about oneself. • Experimenter bias: the researcher’s expectations about the outcome of the study affect the outcome • the double-blind solution

29. Population and Sample • Population: the larger collection of people from which a sample is drawn and that researchers want to generalize about. • Sample: the collection of subjects selected for observation in an empirical study

30. Figure 2.16 The relationship between the population and the sample

31. Ethics in Psychological Research:Do the Ends Justify the Means? • The question of deception • The question of animal research • Controversy among psychologists and the public • Ethical standards for research: the American Psychological Association • Ensures both human and animal subjects are treated with dignity

32. Figure 2.17 Ethics in research